When To Use EM Algorithm
- Data is only partially observable.
- Unsupervised clustering (target value unobservable).
- Supervised learning (some instance attributes unobservable).
- Can be used to:
- Train Bayesian Belief Networks.
- Unsupervised clustering (AUTOCLASS).
- Learning Hidden Markov Models.
José M. Vidal
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